Surgical Needle Pose Estimation for Robotic Suturing
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Solution Overview
Problem
Robotic surgical suturing is cognitively challenging due to difficulties in locating appropriate needle penetration points, grasping needles perpendicularly, envisioning needle trajectories, approximating tissue, inserting needles, rotating them, and tying sutures, especially with curved or flexible tools, which increases the cognitive load on surgeons.
Innovation Solution
A system that includes an imaging device and control unit with a processor and memory to capture and process images of surgical needles and tools, estimate their poses, generate augmented images, and adjust needle trajectories using machine learning networks to provide real-time guidance and control signals for improved suturing outcomes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If robotic surgical suturing is performed with curved or flexible tools, then surgical capability is enhanced, but cognitive load on surgeons increases
Solution Approach 1:
The patent introduces an imaging device and control unit as an intermediary between the surgeon and the robotic surgical system. The imaging device captures images of the surgical needle and tool, while the control unit processes these images to estimate poses and generate augmented images with trajectory guidance. This intermediary system handles the complexity of interpreting curved needle paths and tool orientations, reducing the cognitive burden on the surgeon while maintaining enhanced surgical capability.
Solution Approach 2:
The patent replaces manual mechanical judgment and visualization with an automated imaging and processing system. Instead of relying on the surgeon's cognitive abilities to envision needle trajectories and estimate poses, the system uses image capture, processing, and augmented reality visualization to provide real-time guidance. This substitution of mechanical/cognitive processes with automated systems resolves the contradiction by maintaining surgical versatility while reducing cognitive load.
2Measurement precision
If real-time image processing and pose estimation are implemented, then guidance accuracy is improved, but system complexity increases
Solution Approach 1:
The control unit is designed as a multi-functional system that performs multiple tasks: capturing images, processing images, estimating needle pose, estimating tool pose, generating augmented images, and providing trajectory guidance. By consolidating these functions into a single control unit, the system achieves high guidance accuracy through comprehensive image processing while managing overall system complexity through functional integration rather than proliferation of separate components.
Data Source
AI summary
A system for tissue suturing guidance in a surgical site includes an imaging device configured to capture an image of a surgical needle within the surgical site and an imaging device control unit configured to control the imaging device. The imaging device control unit includes a processor and a memory. The memory stores instructions which, when executed by the processor, cause the system to capture an image of a surgical needle and a surgical tool within the surgical site via the imaging device, estimate a pose of the surgical needle based on the captured image, generate an augmented image based on the estimated pose of the surgical needle, and display on a display, the augmented image of the surgical needle